NEW! Cloud

Developers have been the first to take advantage of public clouds to explore new application architectures, test programming concepts, quickly and inexpensively introduce new applications, and create test beds for analyzing performance and scalability.This track examines innovative application architectures for development using cloud approaches, how to analyze and test applications and application components in the cloud, and development challenges unique to the cloud. Learn how to utilize the cloud in building new application architectures and testing applications in the cloud.

Cloud sessions already confirmed:

• Cloud Computing with Scala and GridGain
• Developing with Amazon WS - Highly Scalable Services that are Someone Else's Headache to Maintain and Develop
• Mix It Up in the Cloud: ServiceMix Solution for SaaS
• Running Java and Grails Applications on the Amazon Elastic Compute Cloud (EC2)
• Using Java Parallel Method Invocation to Accelerate Data Analysis on a Distributed Data Grid

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Cloud Computing with Scala and GridGain

Nikita Ivanov, Founder, GridGain

Scala is a hybrid function and object-oriented language that is rapidly gaining traction in becoming the “next” Java in JVM-based language evolution. GridGain is one of the most rapidly growing cloud development platforms for JVM-based languages. These 2 trends could define business application development for years to come.

The topic of this session is how to use the Scala programming language with GridGain’s cloud development platform to provide a simple and productive cloud computing platform. Nikita Ivanov devotes two-thirds of the session to live coding demonstrations of writing basic MapReduce applications in Scala using GridGain middleware. He starts by providing an overview of grid and cloud computing concepts, the idea of Native Cloud Applications, and a short introduction to the Scala language.

You learn how to:

• Build and run simple Scala MapReduce applications;
• Start and configure GridGain;
• Cloud-enable the existing Scala code using GridGain to run it on the cloud;
• And more.

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Developing with Amazon WS – Highly Scalable Services that are Someone Else’s Headache to Maintain and Develop

Chris Richardson, Head of Cloud Development, SpringSource

The Amazon Elastic Compute Cloud (EC2) is probably the best known Web service from Amazon, but it’s not the only one. There are other highly scalable and reliable Web services that you can use in your Java applications including the Simple Storage Service (S3), Simple Queuing Service (SQS) and SimpleDB, a non-relational database. Although, using these Web services couples your application to Amazon, they let you build highly scalable applications without the pain and cost of having to develop your own infrastructure.

In this session you learn:

• How to use Amazon EC2, Simple Storage Service (S3), Simple Queuing Service (SQS) and SimpleDB;
• The various open source Java libraries for interacting with these Web services, including JetS3t and Typica;
• The benefits and drawbacks of these Web services and their typical use cases;
• And more.

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Mix it Up in the Cloud: ServiceMix Solution for SaaS

Heath Kesler, Open Source Software Evangelist

With all the hype behind the cloud and many software vendors looking to provide their software as a service, there is a growing need for integrating these vendor specific software services. Learning how to identify and solve security issues is paramount to any cloud-based solution. And getting knowledge up front on how to design, implement and deploy solutions from real-world examples will save time and money for those wishing ride the cloud. 

This session examines a use case of a real-world problem in the healthcare industry and demonstrates a long-term solution. Heath Kesler sheds light on how to architect an ESB aimed at Software as a Service (SaaS) for the cloud and covers basic security concerns and generic deployment options within the cloud that are viable for an enterprise software solution.

This session reveals:

• A real-world example of an ESB/Cloud implementation;
• An in-depth use case of a major healthcare problem;
• How to use ServiceMix as ESB solution in the cloud;
• How to deploy a SaaS solution to the cloud;
• How to identify and solve security issues in cloud-based solutions.

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Running Java and Grails Applications on the Amazon Elastic Compute Cloud

Chris Richardson, Head of Cloud Development, SpringSource

The Amazon Elastic Compute Cloud (EC2) is ideally suited to running Java applications. It lets you develop using standard Java software packages such as Tomcat and MySQL and rapidly deploy applications on servers that are provisioned and managed via a web services API. And, with its pay-as-you-go pricing model, Amazon EC2 enables startups to launch their application without any upfront investment in computer hardware - and allows enterprises to reduce costs and become more agile.

However, because it is a cloud, some aspects of Amazon EC2 are very different than a traditional, physical computing environment. This session explores those differences, including:

• How the cloud impacts security, networking, storage and availability;
• How to use EC2 and the other Amazon Web services to develop and deploy Java applications;
• How to use EC2 availability zones to deploy highly available applications;
• How to architect secure applications for Amazon EC2.

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Using Java Parallel Method Invocation to Accelerate Data Analysis on a Distributed Data Grid

Bill Bain, Founder & CEO, ScaleOut Software

Data parallel programming on a distributed data grid is an important new method for overcoming performance bottlenecks for a broad class of applications. This new method is expected to have important applications in cloud computing over the next few years.

Parallel programming expert, Bill Bain shows you how a distributed data grid can be used to implement powerful, Java-based applications for parallel data analysis. In this session he introduces the use of distributed data grids from the perspective of a Java developer. He examines various uses for data grids in scaling application performance and gives specific examples of measured performance. Bill then demonstrates how a Java parallel data analysis application is constructed using the map/reduce programming paradigm. A real-world case study is illustrated, and the execution plan and performance benefits are shown. Finally, potential future applications of this technology in cloud infrastructures are described.

This session addresses the following:

• What are distributed data grids and how do they help applications scale performance?
• How can data parallel applications designed for data grids be written in Java?
• How is scalable throughput measured, and what are the key performance bottlenecks?
• What applications can benefit from this parallel programming method, and what is the importance of this method for cloud computing?